Enhanced Detection of Antigen-Specific CD4+ T Cells Using Altered Peptide Flanking Residue Peptide–MHC Class II Multimers
Bibliographic record
Abstract
Fluorochrome-conjugated peptide-MHC (pMHC) class I multimers are staple components of the immunologist's toolbox, enabling reliable quantification and analysis of Ag-specific CD8(+) T cells irrespective of functional outputs. In contrast, widespread use of the equivalent pMHC class II (pMHC-II) reagents has been hindered by intrinsically weaker TCR affinities for pMHC-II, a lack of cooperative binding between the TCR and CD4 coreceptor, and a low frequency of Ag-specific CD4(+) T cell populations in the peripheral blood. In this study, we show that peptide flanking regions, extending beyond the central nonamer core of MHC-II-bound peptides, can enhance TCR-pMHC-II binding and T cell activation without loss of specificity. Consistent with these findings, pMHC-II multimers incorporating peptide flanking residue modifications proved superior for the ex vivo detection, characterization, and manipulation of Ag-specific CD4(+) T cells, highlighting an unappreciated feature of TCR-pMHC-II interactions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".